"A guide to finding data in public databases" matching MCP servers:

Enables AI agents to control and interact with a local Windows computer through authenticated MCP tools, including file operations, shell commands, process management, HTTP requests, and system/media inspection.

Enables AI agents to securely connect to and manage remote servers via SSH, with tools for running commands, file operations, log inspection, service management, and system monitoring under configurable access controls and audit logging.

Enables bounded agent authority over a macOS workstation via 63 MCP tools with policy, approval, and audit.

A local MCP runtime for macOS and Windows that enables ChatGPT to read, edit, search, run tests, and capture screenshots in your local project folder while keeping your source code on your machine.

Provides secure filesystem access for AI models through the Model Context Protocol with strict path validation, file operations, directory management, and system command execution within predefined directories.

A simple MCP server that exposes a terminal tool, allowing AI agents to execute shell commands.

The m2m-mcp-server-ssh-client provides a unified MCP server interface, securely connecting via SSH to the m2m-mcp-server-ssh-server back-end which aggregates MCP servers. This setup offers secure, single-point access to diverse remote tools using robust SSH key-based authentication.

Enables ChatGPT Web conversations to operate a Windows computer through MCP with local tools, permissions, task state, and audit evidence.

An MCP server that enables AI assistants to execute shell commands and manage files on remote servers via SSH. It supports recursive directory uploads, archive extraction, and direct file creation from text content.

Enables agents to spawn, monitor, and control CLI coding agents running in isolated tmux sessions, with verified input injection, redacted pane capture, fleet and per-session state classification, lineage tracking, blocking exec with exit codes, cross-agent messaging, waste analytics, and log/ledger reading. Ownership checks, policy controls, and audit events keep every control action safe by default.

A self-hosted MCP server that enables AI coding agents to read, edit, search, and run code in local projects with human review loops and policy controls.

Enables MCP-compatible AI clients to connect to a Windows machine for file operations, PowerShell execution, Git inspection, task management, memory, and skills.

An MCP server that connects Claude Desktop to an interactive Claude Code session running in a tmux terminal.

A FastMCP server that enables AI agents to safely execute shell commands, run code in Python/Node.js/Go, and install packages, all packaged in Docker for secure deployment.

Enables reading diagnostic data from remote servers over SSH using a whitelist of read-only commands, with secret redaction.

Runs commands on machines you cannot SSH into by publishing steps to a transport the far side already reaches (git, file share, S3, relay), then reads back a log with every line timestamped in UTC. Seven tools cover send, status, logs, stall detection and a pre-flight check.

Enables AI clients to manage remote Linux workspaces over OpenSSH, including file read/write/edit, glob/grep search, shell command execution, and background job management, with authentication handled interactively in a terminal.

A Python MCP server that provides controlled access to local filesystem, terminal, processes, and SAP HANA Cloud, enabling Claude to interact with your machine and databases securely.

Exposes Mavis's coding tools (bash, edit, git, supabase) to Claude Code via the Model Context Protocol, enabling Claude to reason and execute commands in a sandboxed workspace.

Provides a governed command plane for MCP agents to manage PostgreSQL databases, SSH sessions, and HTTP APIs with encrypted credential storage and prescriptive workflows.